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Note that in that preview, the ‘tabbed layout’ that makes, for example, userfriendly inspection of the pairwise scatterplots possible, does not work (perhaps GitHub Preview blocks javascript?), so you may want to download the rendered .html in any case.
### Import using haven
dat <-
haven::read_sav(file.path(dataPath,
'database.orig.new labels.sav'));
### ... But convert to a data frame instead of a tibble, because,
### for example, length(unique(dat[, 'group'])) results in 1 instead
### of 2...
dat <- as.data.frame(dat);
dat <- haven::zap_label(dat);
dat <- haven::zap_labels(dat);
### Set group as factor
dat$group <-
factor(dat$group,
levels=1:2,
labels=c("Alternative medicine",
"Medicine"));
dat$group_tri <-
ifelse(dat$group=="Medicine",
1,
ifelse(dat$TCM6_simult < 3,
2,
ifelse(dat$TCM6_simult > 2,
3,
NA)));
dat$group_tri <-
factor(dat$group_tri,
levels=1:3,
labels=c("Biomed",
"Alternative",
"Complementary"));
### Extract and store attitude variable names
attitudeVars <-
grep('ATT1_',
names(dat),
value=TRUE);
attitudeVars_2 <-
grep('ATT2_',
names(dat),
value=TRUE);
constructTreeYAML <-
yum::load_yaml_fragments(here::here("methods-construct-tree",
"cam-biomed-attitude-tree-1.dct"));
constructTree <-
yum::build_tree(constructTreeYAML);
constructTree$Do(function(node) {
nameFromDataset <-
grep(node$name,
names(dat),
value=TRUE);
print(nameFromDataset);
if (length(nameFromDataset) > 0) {
node$label <- nameFromDataset;
}},
filterFun = data.tree::isLeaf);
## [1] "ATT1_4_BodyMirrorToSoul"
## [1] "ATT1_31_IllnessSymbology"
## [1] "ATT1_21_IllnessBecauseOfEmotions"
## [1] "ATT1_33_SymptomsWillDisappear"
## [1] "ATT1_9_MindHasStrongEffect"
## [1] "ATT1_11_BodyRemembers"
## [1] "ATT1_36_UnprocessedTrauma"
## [1] "ATT1_28_ConfrontingEmotionalProb"
## [1] "ATT1_26_HealingResultOfEmoDevelopment"
## [1] "ATT1_18_TreatsOnlySymptoms"
## [1] "ATT1_17_SickByChance"
## [1] "ATT1_20_HealingIsLuck"
## [1] "ATT1_10_AttractPplAndEvents"
## [1] "ATT1_16_EverythingConnected"
## [1] "ATT1_23_NothingByChance"
## [1] "ATT1_2_MustSuffer"
## [1] "ATT1_38_IllnessTeachesUs"
## [1] "ATT1_34_EnergyInEastern"
## [1] "ATT1_27_EnergeticSystemInBody"
## [1] "ATT1_14_Reincarnation"
## [1] "ATT1_6_IllnessIsImbalance"
## [1] "ATT1_40_StrongerComplaintsMeanHealing"
## [1] "ATT1_29_RadiationTherapyHarmful"
## [1] "ATT1_25_ChemotherapyHarmful"
## [1] "ATT1_39_OnlyNatural"
## [1] "ATT1_22_AvoidPharma"
## [1] "ATT1_37_NoBiopsy"
## [1] "ATT1_30_MandatoryVaccines"
## [1] "ATT1_15_TrustAncientRemedies"
## [1] "ATT1_3_TrustInTradRemedy"
## [1] "ATT1_13_ElectronicRadiation"
## [1] "ATT1_7_HealthyDiet"
## [1] "ATT1_1_ExerciseAndDiet"
## [1] "ATT1_12_WeakImmuneSystem"
## [1] "ATT1_24_IllnessBecauseOfGenes"
## [1] "ATT1_32_TrustWesternDocs"
## [1] "ATT1_35_SeriousSymptom"
## [1] "ATT1_5_DependsOnEnvironment"
## [1] "ATT1_19_DoctorMustHealMe"
## [1] "ATT1_8_NeedTestResult"
### Set labels as names
constructTree$Do(function(node) node$name <-
node$label);
### Convert to DiagrammeR graph
constructGraph <-
data.tree::ToDiagrammeRGraph(constructTree);
### Show graph
DiagrammeR::render_graph(constructGraph);
### Export graph
DiagrammeR::export_graph(constructGraph,
file_name = here::here("methods-construct-tree",
"cam-biomed-attitude-tree-1.png"));
### Also plot as dendrogram (method not exported by this version of data.tree, oddly)
constructDendro <-
data.tree:::as.dendrogram.Node(constructTree);
### Get labels in same order
constructTreeLabels <-
unlist(constructTree$Get('label', filterFun=data.tree::isLeaf));
### For future reference: check
### http://www.sthda.com/english/wiki/beautiful-dendrogram-visualizations-in-r-5-must-known-methods-unsupervised-machine-learning#ggdendro-package-ggplot2-and-dendrogram
ggConstructDendro1 <-
ggdendro::ggdendrogram(constructDendro,
rotate=TRUE,
theme_dendro = TRUE) +
ggplot2::scale_x_continuous(position="top",
breaks=seq_along(constructTreeLabels),
labels=constructTreeLabels) +
ggplot2::scale_y_reverse();
## Scale for 'x' is already present. Adding another scale for 'x', which
## will replace the existing scale.
## Scale for 'y' is already present. Adding another scale for 'y', which
## will replace the existing scale.
print(ggConstructDendro1);
ggsave(filename=here::here("methods-construct-tree",
"cam-biomed-dendrogram-1.png"),
plot=ggConstructDendro1,
width=12,
height=19,
units='cm');
ggConstructDendro2 <-
constructDendro %>%
dendextend::set("branches_k_color",
value = viridis::viridis(4),
k = 4) %>%
dendextend::as.ggdend() %>%
ggplot2::ggplot(horiz=TRUE);
print(ggConstructDendro2);
## Warning: Removed 69 rows containing missing values (geom_point).
ggsave(filename=here::here("methods-construct-tree",
"cam-biomed-dendrogram-2.png"),
plot=ggConstructDendro2,
width=40,
height=30,
units='cm');
## Warning: Removed 69 rows containing missing values (geom_point).
ufs::cat0("\n\n#### Missing values\n\n");
apply(is.na(dat[, attitudeVars]), 2, sum);
ATT1_1_ExerciseAndDiet
0
ATT1_2_MustSuffer
0
ATT1_3_TrustInTradRemedy
0
ATT1_4_BodyMirrorToSoul
0
ATT1_5_DependsOnEnvironment
0
ATT1_6_IllnessIsImbalance
0
ATT1_7_HealthyDiet
0
ATT1_8_NeedTestResult
0
ATT1_9_MindHasStrongEffect
0
ATT1_10_AttractPplAndEvents
0
ATT1_11_BodyRemembers
0
ATT1_12_WeakImmuneSystem
0
ATT1_13_ElectronicRadiation
0
ATT1_14_Reincarnation
0
ATT1_15_TrustAncientRemedies
0
ATT1_16_EverythingConnected
0
ATT1_17_SickByChance
0
ATT1_18_TreatsOnlySymptoms
0
ATT1_19_DoctorMustHealMe
0
ATT1_20_HealingIsLuck
0
ATT1_21_IllnessBecauseOfEmotions
0
ATT1_22_AvoidPharma
0
ATT1_23_NothingByChance
0
ATT1_24_IllnessBecauseOfGenes
0
ATT1_25_ChemotherapyHarmful
0
ATT1_26_HealingResultOfEmoDevelopment 0 ATT1_27_EnergeticSystemInBody 0 ATT1_28_ConfrontingEmotionalProb 0 ATT1_29_RadiationTherapyHarmful 0 ATT1_30_MandatoryVaccines 0 ATT1_31_IllnessSymbology 0 ATT1_32_TrustWesternDocs 0 ATT1_33_SymptomsWillDisappear 0 ATT1_34_EnergyInEastern 0 ATT1_35_SeriousSymptom 0 ATT1_36_UnprocessedTrauma 0 ATT1_37_NoBiopsy 3 ATT1_38_IllnessTeachesUs 0 ATT1_39_OnlyNatural 0 ATT1_40_StrongerComplaintsMeanHealing 0
ufs::cat0("\n\n#### Attitude\n\n");
ufs::meansComparisonDiamondPlot(dat,
rev(attitudeVars),
compareBy = 'group_tri',
comparisonColors = viridis::viridis(3,
end=.7),
dataAlpha=.25);
This section uses tabs to show descriptives for all variables.
get_descriptives <- function(data,
varName,
headerLevel) {
return(paste0("\n\n",
ufs::repStr("#", headerLevel),
" ", varName, "\n\n",
as.character(pander(userfriendlyscience::descr(data[, varName]))),
"\n\n"));
}
for (currentVar in names(dat)) {
cat(get_descriptives(dat,
currentVar,
headerLevel=4));
}
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 81.96 | 84 | NA | [74.46; 89.46] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2262 | 47.56 | 83 | 3.796 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 39.5 | 123.5 | 162 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.02789 | -1.243 | 0.01473 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
| Frequencies | Perc.Total | Perc.Valid | Cumulative | |
|---|---|---|---|---|
| Alternative medicine | 95 | 60.5 | 60.5 | 60.5 |
| Medicine | 62 | 39.5 | 39.5 | 100 |
| Total valid | 157 | 100 | 100 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1970 | 1973 | 1974 | [1967.55; 1972.66] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 262.4 | 16.2 | 28 | 1.293 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1937 | 1956 | 1984 | 1998 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.2984 | -1.09 | 0.02269 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 46.89 | 44 | 43 | [44.34; 49.45] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 262.4 | 16.2 | 28 | 1.293 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 19 | 33 | 61 | 80 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.2984 | -1.09 | 0.02269 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.72 | 2 | 2 | [1.65; 1.79] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.203 | 0.4506 | 1 | 0.03596 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | NA | 2 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.988 | -1.037 | 0.1401 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.974 | 1 | 1 | [2.62; 3.33] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 4.901 | 2.214 | 4 | 0.1784 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | NA | 5 | 7 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.3445 | -1.749 | 0.1578 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 3 | 154 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.618 | 6 | 6 | [5.48; 5.76] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.7633 | 0.8737 | 1 | 0.06973 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 2 | 4 | 7 | 7 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.623 | 2.652 | 0.06051 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.777 | 3 | 2 | [3.38; 4.18] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 6.431 | 2.536 | 5 | 0.2024 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 7 | 10 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.7341 | -0.9645 | 0.1178 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1263 | 0 | 0 | [0.06; 0.19] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1115 | 0.334 | 0 | 0.03426 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.286 | 3.295 | 0.06316 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.03158 | 0 | 0 | [0; 0.07] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.03091 | 0.1758 | 0 | 0.01804 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 5.444 | 28.23 | 0.01579 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.09474 | 0 | 0 | [0.03; 0.15] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.08667 | 0.2944 | 0 | 0.03021 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.812 | 6.036 | 0.04737 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.02105 | 0 | 0 | [-0.01; 0.05] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.02083 | 0.1443 | 0 | 0.01481 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 6.78 | 44.91 | 0.01053 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.07368 | 0 | 0 | [0.02; 0.13] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.06898 | 0.2626 | 0 | 0.02695 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.316 | 9.19 | 0.03684 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.09474 | 0 | 0 | [0.03; 0.15] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.08667 | 0.2944 | 0 | 0.03021 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.812 | 6.036 | 0.04737 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.03158 | 0 | 0 | [0; 0.07] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.03091 | 0.1758 | 0 | 0.01804 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 5.444 | 28.23 | 0.01579 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.363e+10 | 1.369e+10 | 1.37e+10 | [13597369449.37; 13659067628.89] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.219e+16 | 1.49e+08 | 95904000 | 15530329 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1.291e+10 | 1.361e+10 | 1.371e+10 | 1.372e+10 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -2.892 | 9.319 | 0.03998 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 65 | 92 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 48.19 | 16 | 20 | [29.72; 66.66] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 7688 | 87.68 | 34 | 9.294 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 6 | 45 | 500 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.595 | 15.05 | 0.04494 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 68 | 89 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.338 | 4 | 4 | [3.13; 3.54] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.586 | 1.259 | 2 | 0.1035 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.3728 | -0.914 | 0.1014 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 9 | 148 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.609 | 2 | 1 | [2.36; 2.86] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.498 | 1.58 | 3 | 0.1265 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 4 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.2789 | -1.597 | 0.1306 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 1 | 156 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.8471 | 1 | 0 | [0.69; 1] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.9508 | 0.9751 | 2 | 0.07782 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 0 | 2 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.9845 | 0.8398 | 0.121 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1613 | 0 | 0 | [0.07; 0.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1375 | 0.3708 | 0 | 0.04709 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.888 | 1.615 | 0.08065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1613 | 0 | 0 | [0.07; 0.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1375 | 0.3708 | 0 | 0.04709 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.888 | 1.615 | 0.08065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1774 | 0 | 0 | [0.08; 0.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1483 | 0.3851 | 0 | 0.04891 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.731 | 1.028 | 0.08871 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1613 | 0 | 0 | [0.07; 0.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1375 | 0.3708 | 0 | 0.04709 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.888 | 1.615 | 0.08065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1774 | 0 | 0 | [0.08; 0.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1483 | 0.3851 | 0 | 0.04891 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.731 | 1.028 | 0.08871 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1613 | 0 | 0 | [0.07; 0.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1375 | 0.3708 | 0 | 0.04709 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.888 | 1.615 | 0.08065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
## Warning: Computation failed in `stat_bin()`:
## `binwidth` must be positive
## Warning: Removed 1 rows containing missing values (geom_abline).
## Warning: Computation failed in `stat_bin()`:
## `binwidth` must be positive
## Warning: Removed 1 rows containing missing values (geom_abline).
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0 | 0 | 0 | [0; 0] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0 | 0 | 0 | 0 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | NA | 0 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| NA | NA | 0.008065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.129 | 0 | 0 | [0.04; 0.21] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1142 | 0.338 | 0 | 0.04292 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.268 | 3.25 | 0.06452 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.01613 | 0 | 0 | [-0.02; 0.05] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.01613 | 0.127 | 0 | 0.01613 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 7.874 | 62 | 0.008065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2903 | 0 | 0 | [0.17; 0.41] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2094 | 0.4576 | 1 | 0.05812 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.9469 | -1.141 | 0.1452 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
## Warning: Computation failed in `stat_bin()`:
## `binwidth` must be positive
## Warning: Removed 1 rows containing missing values (geom_abline).
## Warning: Computation failed in `stat_bin()`:
## `binwidth` must be positive
## Warning: Removed 1 rows containing missing values (geom_abline).
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0 | 0 | 0 | [0; 0] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0 | 0 | 0 | 0 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | NA | 0 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| NA | NA | 0.008065 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2097 | 0 | 0 | [0.11; 0.31] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1684 | 0.4104 | 0 | 0.05212 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.462 | 0.1409 | 0.1048 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.3871 | 0 | 0 | [0.26; 0.51] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2411 | 0.4911 | 1 | 0.06236 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4752 | -1.834 | 0.1935 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.09677 | 0 | 0 | [0.02; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.08884 | 0.2981 | 0 | 0.03785 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.796 | 6.01 | 0.04839 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.129 | 0 | 0 | [0.04; 0.21] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1142 | 0.338 | 0 | 0.04292 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.268 | 3.25 | 0.06452 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.08065 | 0 | 0 | [0.01; 0.15] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.07536 | 0.2745 | 0 | 0.03486 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.157 | 8.232 | 0.04032 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2419 | 0 | 0 | [0.13; 0.35] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1864 | 0.4318 | 0 | 0.05483 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.235 | -0.491 | 0.121 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 95 | 62 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.179 | 1 | 1 | [1.1; 1.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1485 | 0.3853 | 0 | 0.03954 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | NA | 2 | 2 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.702 | 0.9162 | 0.08947 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.968 | 2 | 2 | [1.8; 2.13] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.6549 | 0.8092 | 0 | 0.08347 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 1 | 4 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.054 | 5.114 | 0.05319 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.01053 | 0 | 0 | [-0.01; 0.03] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.01053 | 0.1026 | 0 | 0.01053 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 9.747 | 95 | 0.005263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.4526 | 0 | 0 | [0.35; 0.55] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2504 | 0.5004 | 1 | 0.05134 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.1934 | -2.005 | 0.2263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.04211 | 0 | 0 | [0; 0.08] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.04076 | 0.2019 | 0 | 0.02071 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 4.634 | 19.89 | 0.02105 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.4 | 0 | 0 | [0.3; 0.5] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2426 | 0.4925 | 1 | 0.05053 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4148 | -1.868 | 0.2 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.6105 | 1 | 1 | [0.51; 0.71] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2403 | 0.4902 | 1 | 0.0503 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 0 | NA | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.4606 | -1.827 | 0.1947 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2 | 0 | 0 | [0.12; 0.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1617 | 0.4021 | 0 | 0.04126 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.524 | 0.3296 | 0.1 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.5368 | 0 | 0 | [0.37; 0.71] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.6981 | 0.8355 | 1 | 0.08572 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 7 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 4.967 | 37.65 | 0.2316 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.579 | 1 | 1 | [1.44; 1.72] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.4591 | 0.6776 | 1 | 0.06952 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | NA | 2 | 3 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.7547 | -0.5432 | 0.1842 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.08421 | 0 | 0 | [0.03; 0.14] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.07794 | 0.2792 | 0 | 0.02864 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.043 | 7.414 | 0.04211 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1895 | 0 | 0 | [0.11; 0.27] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1552 | 0.394 | 0 | 0.04042 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.61 | 0.6054 | 0.09474 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.04211 | 0 | 0 | [0; 0.08] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.04076 | 0.2019 | 0 | 0.02071 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 4.634 | 19.89 | 0.02105 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.4632 | 0 | 0 | [0.34; 0.59] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.3789 | 0.6156 | 1 | 0.06316 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 4 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.099 | 9.717 | 0.2105 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.02105 | 0 | 0 | [-0.01; 0.05] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.02083 | 0.1443 | 0 | 0.01481 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 6.78 | 44.91 | 0.01053 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.3263 | 0 | 0 | [0.23; 0.42] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2222 | 0.4714 | 1 | 0.04836 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.7528 | -1.465 | 0.1632 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1368 | 0 | 0 | [0.07; 0.21] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1194 | 0.3455 | 0 | 0.03545 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.147 | 2.667 | 0.06842 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2 | 0 | 0 | [0.12; 0.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1617 | 0.4021 | 0 | 0.04126 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.524 | 0.3296 | 0.1 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1368 | 0 | 0 | [0.07; 0.21] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1194 | 0.3455 | 0 | 0.03545 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.147 | 2.667 | 0.06842 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.02105 | 0 | 0 | [-0.01; 0.05] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.02083 | 0.1443 | 0 | 0.01481 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 6.78 | 44.91 | 0.01053 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1053 | 0 | 0 | [0.04; 0.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.09518 | 0.3085 | 0 | 0.03165 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.614 | 4.936 | 0.05263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2632 | 0 | 0 | [0.17; 0.35] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.196 | 0.4427 | 1 | 0.04542 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.093 | -0.823 | 0.1316 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.09474 | 0 | 0 | [0.03; 0.15] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.08667 | 0.2944 | 0 | 0.03021 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.812 | 6.036 | 0.04737 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1579 | 0 | 0 | [0.08; 0.23] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1344 | 0.3666 | 0 | 0.03761 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.907 | 1.67 | 0.07895 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.06316 | 0 | 0 | [0.01; 0.11] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.0598 | 0.2445 | 0 | 0.02509 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.65 | 11.56 | 0.03158 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.01053 | 0 | 0 | [-0.01; 0.03] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.01053 | 0.1026 | 0 | 0.01053 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 9.747 | 95 | 0.005263 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.07368 | 0 | 0 | [0.02; 0.13] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.06898 | 0.2626 | 0 | 0.02695 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.316 | 9.19 | 0.03684 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.3263 | 0 | 0 | [0.23; 0.42] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2222 | 0.4714 | 1 | 0.04836 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.7528 | -1.465 | 0.1632 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.242 | 3 | 3 | [2.02; 2.46] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.185 | 1.089 | 2 | 0.1117 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 4 | 4 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.00604 | -1.51 | 0.1947 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.09574 | 0 | 0 | [0.04; 0.16] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.08751 | 0.2958 | 0 | 0.03051 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.793 | 5.924 | 0.04787 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.03191 | 0 | 0 | [0; 0.07] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.03123 | 0.1767 | 0 | 0.01823 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 5.413 | 27.89 | 0.01596 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1596 | 0 | 0 | [0.08; 0.23] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1356 | 0.3682 | 0 | 0.03797 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.889 | 1.604 | 0.07979 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.06383 | 0 | 0 | [0.01; 0.11] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.0604 | 0.2458 | 0 | 0.02535 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.627 | 11.4 | 0.03191 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1809 | 0 | 0 | [0.1; 0.26] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1497 | 0.387 | 0 | 0.03991 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.685 | 0.8583 | 0.09043 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.08511 | 0 | 0 | [0.03; 0.14] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.0787 | 0.2805 | 0 | 0.02894 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 3.022 | 7.288 | 0.04255 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2979 | 0 | 0 | [0.2; 0.39] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2114 | 0.4598 | 1 | 0.04742 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.8984 | -1.219 | 0.1489 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2021 | 0 | 0 | [0.12; 0.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.163 | 0.4037 | 0 | 0.04164 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.508 | 0.2785 | 0.1011 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1277 | 0 | 0 | [0.06; 0.2] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1126 | 0.3355 | 0 | 0.0346 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.268 | 3.211 | 0.06383 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.663 | 2 | 2 | [2.39; 2.93] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.758 | 1.326 | 2 | 0.136 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 1 | 4 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.1986 | -1.161 | 0.1316 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2553 | 0 | 0 | [0.17; 0.35] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1922 | 0.4384 | 1 | 0.04522 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.141 | -0.7148 | 0.1277 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1383 | 0 | 0 | [0.07; 0.21] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1205 | 0.3471 | 0 | 0.0358 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.13 | 2.59 | 0.06915 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.03191 | 0 | 0 | [0; 0.07] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.03123 | 0.1767 | 0 | 0.01823 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 5.413 | 27.89 | 0.01596 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.01064 | 0 | 0 | [-0.01; 0.03] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.01064 | 0.1031 | 0 | 0.01064 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 9.695 | 94 | 0.005319 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1489 | 0 | 0 | [0.08; 0.22] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1281 | 0.3579 | 0 | 0.03692 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.004 | 2.06 | 0.07447 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.447 | 1 | 1 | [1.32; 1.57] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.3789 | 0.6155 | 1 | 0.06349 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 0 | 2 | 3 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.772 | -0.001887 | 0.1755 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 63 | 94 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1158 | 0 | 0 | [0.05; 0.18] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1035 | 0.3217 | 0 | 0.033 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.44 | 4.039 | 0.05789 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.2105 | 0 | 0 | [0.13; 0.29] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.168 | 0.4098 | 0 | 0.04205 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 1.443 | 0.0835 | 0.1053 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.8 | 1 | 1 | [0.72; 0.88] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1617 | 0.4021 | 0 | 0.04126 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 0 | NA | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.524 | 0.3296 | 0.1 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.1474 | 0 | 0 | [0.07; 0.22] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.127 | 0.3564 | 0 | 0.03656 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 2.022 | 2.132 | 0.07368 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in userfriendlyscience::descr(data[, varName]) : The first argument (called ‘x’ in this function, you passed ‘data[, varName]’) is not a numeric vector (it has class ‘character’). Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.095 | 3 | 3 | [3.01; 3.18] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.1931 | 0.4394 | 0 | 0.04508 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 2 | 2 | 4 | 4 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4819 | 1.949 | 0.07368 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 62 | 95 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.777 | 5 | 5 | [4.59; 4.96] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.405 | 1.185 | 2 | 0.0946 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.359 | 2.064 | 0.1433 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.191 | 3 | 2 | [2.96; 3.42] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.181 | 1.477 | 2 | 0.1179 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.1851 | -0.9792 | 0.1019 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.936 | 4 | 4 | [3.71; 4.17] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.137 | 1.462 | 2 | 0.1167 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.3871 | -0.6568 | 0.1083 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.783 | 5 | 5 | [4.58; 4.98] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.607 | 1.268 | 2 | 0.1012 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3.5 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.191 | 1.049 | 0.1688 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.822 | 3 | 2 | [2.62; 3.02] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.635 | 1.279 | 2 | 0.102 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4.5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4701 | -0.4979 | 0.1401 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.115 | 5 | 6 | [4.96; 5.27] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.9483 | 0.9738 | 1 | 0.07772 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.119 | 1.44 | 0.1624 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.146 | 5 | 5 | [5.02; 5.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.6771 | 0.8229 | 1 | 0.06567 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 2 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.8381 | 0.6823 | 0.1879 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.369 | 5 | 5 | [4.15; 4.59] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.952 | 1.397 | 1 | 0.1115 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.7556 | -0.2016 | 0.1146 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.892 | 5 | 5 | [4.72; 5.07] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.213 | 1.101 | 2 | 0.08788 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.067 | 0.9044 | 0.1688 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.554 | 5 | 5 | [4.35; 4.76] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.71 | 1.308 | 2 | 0.1044 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.9558 | 0.491 | 0.1306 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.65 | 5 | 5 | [4.47; 4.83] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.344 | 1.159 | 2 | 0.09254 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.7074 | 0.1781 | 0.1369 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.72 | 4 | 3 | [3.51; 3.93] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.806 | 1.344 | 2 | 0.1072 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.1652 | -0.7391 | 0.1242 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.72 | 4 | 3 | [3.51; 3.93] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.729 | 1.315 | 2 | 0.1049 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.03481 | -0.6786 | 0.1274 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.255 | 3 | 1 | [2.97; 3.53] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 3.153 | 1.776 | 3 | 0.1417 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.192 | -1.323 | 0.08599 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.478 | 3 | 3 | [3.27; 3.69] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.764 | 1.328 | 1 | 0.106 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.06782 | -0.5476 | 0.1306 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.637 | 5 | 6 | [4.43; 4.84] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.694 | 1.302 | 2 | 0.1039 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.7644 | 0.05167 | 0.1401 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.255 | 2 | 1 | [2.07; 2.44] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.422 | 1.192 | 2 | 0.09517 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 3 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.8727 | 0.608 | 0.1465 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.631 | 4 | 3 | [3.39; 3.87] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.273 | 1.508 | 2 | 0.1203 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.08928 | -0.9218 | 0.1019 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.268 | 3 | (multi) | [3.07; 3.47] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.62 | 1.273 | 2 | 0.1016 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.04364 | -0.4666 | 0.1465 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 1.962 | 2 | 1 | [1.81; 2.12] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.9472 | 0.9733 | 2 | 0.07768 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 3 | 5 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.88 | 0.3997 | 0.172 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.917 | 4 | 4 | [3.68; 4.15] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.179 | 1.476 | 2 | 0.1178 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2.5 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.437 | -0.579 | 0.1115 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.344 | 5 | 5 | [4.13; 4.56] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.868 | 1.367 | 2 | 0.1091 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.491 | -0.6179 | 0.1242 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.446 | 5 | (multi) | [4.22; 4.67] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.082 | 1.443 | 2 | 0.1152 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.8566 | 0.01703 | 0.1401 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.726 | 3 | (multi) | [2.55; 2.9] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.213 | 1.101 | 1 | 0.0879 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.3874 | -0.0781 | 0.1592 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.739 | 4 | 3 | [3.51; 3.97] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.092 | 1.446 | 2 | 0.1154 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.003063 | -0.7741 | 0.1083 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.293 | 3 | 3 | [3.08; 3.51] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.85 | 1.36 | 2 | 0.1085 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.05794 | -0.64 | 0.1242 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.255 | 5 | 6 | [4; 4.51] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.653 | 1.629 | 3 | 0.13 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.6897 | -0.6408 | 0.121 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.745 | 4 | 4 | [3.52; 3.97] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.089 | 1.445 | 2 | 0.1153 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.2159 | -0.6972 | 0.1146 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.758 | 4 | 3 | [3.54; 3.98] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.98 | 1.407 | 2 | 0.1123 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.05024 | -0.6376 | 0.121 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.968 | 3 | 1 | [2.71; 3.23] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.736 | 1.654 | 2 | 0.132 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4301 | -0.9812 | 0.1051 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.567 | 4 | (multi) | [3.31; 3.82] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.593 | 1.61 | 3 | 0.1285 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.1082 | -1.113 | 0.09873 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.917 | 4 | 4 | [3.72; 4.12] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.576 | 1.256 | 2 | 0.1002 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.4127 | 0.07021 | 0.1242 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.86 | 4 | 4 | [3.67; 4.05] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.416 | 1.19 | 2 | 0.09497 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 3 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.3495 | -0.1385 | 0.1146 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.28 | 4 | 5 | [4.07; 4.49] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.703 | 1.305 | 1 | 0.1041 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.9198 | 0.5815 | 0.1561 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.185 | 4 | 5 | [3.95; 4.41] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.126 | 1.458 | 2 | 0.1164 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.6028 | -0.4739 | 0.121 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.688 | 5 | 5 | [4.51; 4.86] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.216 | 1.103 | 2 | 0.08801 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.8067 | 0.6382 | 0.1306 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.623 | 3 | 1 | [2.39; 2.86] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.145 | 1.465 | 3 | 0.118 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.487 | -0.7611 | 0.1266 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 3 | 154 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.745 | 4 | 4 | [3.51; 3.98] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.153 | 1.467 | 2 | 0.1171 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2.5 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.24 | -0.8165 | 0.1115 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.191 | 3 | 3 | [2.98; 3.4] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.822 | 1.35 | 2 | 0.1077 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.1213 | -0.6503 | 0.1019 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.076 | 3 | 3 | [2.86; 3.29] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.84 | 1.357 | 2 | 0.1083 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.2812 | -0.5233 | 0.09873 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.981 | 5 | 5 | [4.82; 5.14] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.07 | 1.034 | 2 | 0.08256 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.439 | 3.107 | 0.172 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.14 | 4 | 5 | [3.91; 4.37] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.083 | 1.443 | 2 | 0.1152 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.5336 | -0.5584 | 0.1242 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.287 | 5 | 5 | [5.18; 5.4] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.475 | 0.6892 | 1 | 0.05501 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 3 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.5636 | -0.2836 | 0.207 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.724 | 3 | (multi) | [2.51; 2.94] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.904 | 1.38 | 1.5 | 0.1105 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.6425 | -0.1952 | 0.1346 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 1 | 156 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.154 | 5 | 5 | [5.03; 5.28] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.6342 | 0.7964 | 1 | 0.06376 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -1.215 | 3.772 | 0.1763 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 1 | 156 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.353 | 2 | 2 | [2.16; 2.55] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.481 | 1.217 | 2 | 0.09745 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 1 | 3 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.8602 | 0.4026 | 0.141 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 1 | 156 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.739 | 5 | 5 | [4.59; 4.89] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.8737 | 0.9347 | 1 | 0.0746 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 2 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.5043 | 0.08542 | 0.1465 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 3.477 | 3 | 3 | [3.22; 3.74] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 2.654 | 1.629 | 3 | 0.1308 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | 1 | 5 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.1007 | -0.9967 | 0.1 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 2 | 155 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 2.994 | 3 | 3 | [2.79; 3.2] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.64 | 1.281 | 2 | 0.1032 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 2 | 4 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.3337 | -0.3882 | 0.1266 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 3 | 154 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 5.459 | 6 | 6 | [5.35; 5.56] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.4422 | 0.665 | 1 | 0.05307 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 3 | 5 | NA | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.9726 | 0.376 | 0.1847 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 4.369 | 5 | 4 | [4.15; 4.59] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 1.978 | 1.406 | 1 | 0.1122 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 1 | 4 | 6 | 6 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| -0.7513 | -0.09932 | 0.1306 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
## Warning in max(freqs): no non-missing arguments to max; returning -Inf
## Warning in qt(res$intermediate$alpha/2, df = n - 1): NaNs produced
## Warning in qt(1 - res$intermediate$alpha/2, df = n - 1): NaNs produced
Quitting from lines 237-254 (network-analysis-of-alternative-medicine-attitudes.Rmd) Error in data.frame(mean = mean(x), median = median(x), mode = mode, meanCI = meanCi) : arguments imply differing number of rows: 1, 0 Calls:
Describing the central tendency:
| mean | median | mode | 95% CI mean |
|---|---|---|---|
| 0.3949 | 0 | 0 | [0.32; 0.47] |
Describing the spread:
| var | sd | iqr | se |
|---|---|---|---|
| 0.2405 | 0.4904 | 1 | 0.03914 |
Describing the range:
| min | q1 | q3 | max |
|---|---|---|---|
| 0 | NA | 1 | 1 |
Describing the distribution shape:
| skewness | kurtosis | dip |
|---|---|---|
| 0.4341 | -1.835 | 0.1975 |
Describing the sample size:
| total | NA. | valid |
|---|---|---|
| 157 | 0 | 157 |
| Frequencies | Perc.Total | Perc.Valid | Cumulative | |
|---|---|---|---|---|
| Biomed | 62 | 39.5 | 39.5 | 39.5 |
| Alternative | 45 | 28.7 | 28.7 | 68.2 |
| Complementary | 50 | 31.8 | 31.8 | 100 |
| Total valid | 157 | 100 | 100 |
### Takes way too long, huge, etc
# GGally::ggpairs(dat[, attitudeVars]);
cors <- cor(dat[, attitudeVars],
use='complete.obs');
knitr::kable(cors);
| ATT1_1_ExerciseAndDiet | ATT1_2_MustSuffer | ATT1_3_TrustInTradRemedy | ATT1_4_BodyMirrorToSoul | ATT1_5_DependsOnEnvironment | ATT1_6_IllnessIsImbalance | ATT1_7_HealthyDiet | ATT1_8_NeedTestResult | ATT1_9_MindHasStrongEffect | ATT1_10_AttractPplAndEvents | ATT1_11_BodyRemembers | ATT1_12_WeakImmuneSystem | ATT1_13_ElectronicRadiation | ATT1_14_Reincarnation | ATT1_15_TrustAncientRemedies | ATT1_16_EverythingConnected | ATT1_17_SickByChance | ATT1_18_TreatsOnlySymptoms | ATT1_19_DoctorMustHealMe | ATT1_20_HealingIsLuck | ATT1_21_IllnessBecauseOfEmotions | ATT1_22_AvoidPharma | ATT1_23_NothingByChance | ATT1_24_IllnessBecauseOfGenes | ATT1_25_ChemotherapyHarmful | ATT1_26_HealingResultOfEmoDevelopment | ATT1_27_EnergeticSystemInBody | ATT1_28_ConfrontingEmotionalProb | ATT1_29_RadiationTherapyHarmful | ATT1_30_MandatoryVaccines | ATT1_31_IllnessSymbology | ATT1_32_TrustWesternDocs | ATT1_33_SymptomsWillDisappear | ATT1_34_EnergyInEastern | ATT1_35_SeriousSymptom | ATT1_36_UnprocessedTrauma | ATT1_37_NoBiopsy | ATT1_38_IllnessTeachesUs | ATT1_39_OnlyNatural | ATT1_40_StrongerComplaintsMeanHealing | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ATT1_1_ExerciseAndDiet | 1.0000000 | 0.0054161 | 0.0687178 | 0.4206610 | -0.0414439 | 0.2658708 | 0.2202788 | -0.0967743 | 0.2122778 | 0.0760936 | 0.1892129 | 0.1034782 | 0.0197600 | 0.0730772 | 0.1222786 | 0.1458379 | 0.0062962 | 0.1090275 | 0.0362593 | -0.1254873 | 0.2249561 | 0.1121921 | 0.1596211 | -0.0164830 | 0.1906475 | 0.2045420 | 0.1596584 | 0.2316194 | 0.1872051 | -0.0340306 | 0.1517998 | -0.0290251 | 0.1898578 | 0.0832831 | -0.1314154 | 0.0743992 | 0.0377949 | 0.1966049 | 0.1688695 | 0.1461166 |
| ATT1_2_MustSuffer | 0.0054161 | 1.0000000 | 0.0399843 | 0.1360426 | 0.3293624 | 0.0756668 | -0.0443301 | 0.0252070 | 0.0776545 | 0.0814977 | 0.0262516 | 0.1212355 | 0.0694189 | -0.0522676 | -0.0062933 | 0.0418795 | 0.1082750 | -0.0678401 | 0.0841814 | -0.0273832 | -0.0240271 | -0.0610453 | 0.0322213 | 0.0786162 | 0.1472411 | 0.0347830 | -0.0862025 | -0.0507096 | 0.1495866 | 0.0462063 | -0.0716466 | -0.0212468 | -0.0415685 | -0.0987391 | 0.0115117 | 0.0925523 | -0.0252680 | -0.0220949 | -0.0304308 | -0.0737804 |
| ATT1_3_TrustInTradRemedy | 0.0687178 | 0.0399843 | 1.0000000 | 0.2249171 | -0.0482545 | 0.2019742 | 0.0566226 | -0.3493843 | 0.3472783 | 0.2674716 | 0.3485551 | -0.0169306 | 0.1413999 | 0.3188806 | 0.4925796 | 0.2322353 | -0.2312852 | 0.3851676 | 0.0061853 | -0.2851330 | 0.2227620 | 0.3985563 | 0.3275579 | -0.2124415 | 0.3874647 | 0.2926369 | 0.3538216 | 0.2801188 | 0.4184651 | 0.2686508 | 0.3136477 | -0.5087061 | 0.1984842 | 0.2455830 | -0.5663668 | 0.2266169 | 0.2334781 | 0.3287663 | 0.4951061 | 0.3783619 |
| ATT1_4_BodyMirrorToSoul | 0.4206610 | 0.1360426 | 0.2249171 | 1.0000000 | 0.2644718 | 0.4779496 | 0.2469704 | -0.1773445 | 0.4429715 | 0.4876800 | 0.5360377 | 0.1440485 | 0.2358389 | 0.2801344 | 0.2823573 | 0.4375893 | -0.0647945 | 0.2574385 | -0.0264387 | -0.1218190 | 0.4357582 | 0.2865663 | 0.4246552 | -0.0219990 | 0.2648194 | 0.4122420 | 0.3586105 | 0.4398906 | 0.3409473 | 0.1974204 | 0.3989796 | -0.1081250 | 0.4612814 | 0.3063318 | -0.2116695 | 0.4052624 | 0.1882564 | 0.3545914 | 0.2240950 | 0.2303519 |
| ATT1_5_DependsOnEnvironment | -0.0414439 | 0.3293624 | -0.0482545 | 0.2644718 | 1.0000000 | 0.1200548 | -0.1975226 | 0.0830335 | 0.2045356 | 0.1821657 | 0.0094967 | 0.1873449 | -0.0446195 | -0.0713644 | -0.0171854 | 0.0381642 | 0.2457939 | -0.1112211 | 0.2337019 | 0.2034428 | 0.1415459 | -0.1093726 | 0.0530034 | 0.2104045 | -0.0806387 | 0.1341475 | 0.0425695 | 0.0881977 | 0.0095487 | 0.1065393 | 0.0068710 | 0.0294318 | 0.1044473 | 0.0123156 | -0.0079130 | 0.0407223 | 0.1606185 | 0.0722145 | -0.0351267 | -0.0293130 |
| ATT1_6_IllnessIsImbalance | 0.2658708 | 0.0756668 | 0.2019742 | 0.4779496 | 0.1200548 | 1.0000000 | 0.2251774 | -0.1567106 | 0.4942181 | 0.3714301 | 0.5247270 | 0.2674479 | 0.2621854 | 0.2540184 | 0.3298663 | 0.4027674 | -0.1979819 | 0.3487299 | -0.0609286 | -0.1203476 | 0.5529565 | 0.3709777 | 0.4331098 | 0.0769675 | 0.3507904 | 0.4152025 | 0.4152410 | 0.4767843 | 0.3305618 | 0.2681004 | 0.5140983 | -0.2432006 | 0.4812476 | 0.3079574 | -0.2762678 | 0.5847060 | 0.1759754 | 0.4818995 | 0.2912395 | 0.2816260 |
| ATT1_7_HealthyDiet | 0.2202788 | -0.0443301 | 0.0566226 | 0.2469704 | -0.1975226 | 0.2251774 | 1.0000000 | -0.0577381 | 0.1661579 | 0.0937240 | 0.2816853 | 0.0937958 | 0.2443342 | 0.1965104 | 0.0586149 | 0.0950937 | -0.1742249 | 0.1239174 | -0.2131927 | -0.0270183 | 0.1236547 | 0.2317797 | 0.1740472 | -0.1791752 | 0.1441873 | 0.1831216 | 0.2162358 | 0.1749697 | 0.1290462 | 0.0485263 | 0.2555365 | -0.0503647 | 0.1477357 | 0.0778997 | -0.1119189 | 0.2489982 | 0.0698320 | 0.2527524 | 0.1982211 | 0.1957129 |
| ATT1_8_NeedTestResult | -0.0967743 | 0.0252070 | -0.3493843 | -0.1773445 | 0.0830335 | -0.1567106 | -0.0577381 | 1.0000000 | -0.0520796 | -0.1485616 | -0.1486377 | 0.0247272 | -0.0167402 | -0.1849931 | -0.2613940 | -0.1658542 | 0.0969698 | -0.2789160 | 0.2018276 | 0.1247677 | -0.1018884 | -0.2362467 | -0.2229017 | 0.1715445 | -0.2803159 | -0.1360690 | -0.2433245 | -0.2243612 | -0.2923480 | -0.1034996 | -0.2434594 | 0.3172283 | -0.1670566 | -0.1592532 | 0.4402867 | -0.0444246 | -0.0619809 | -0.1714422 | -0.2775466 | -0.1582221 |
| ATT1_9_MindHasStrongEffect | 0.2122778 | 0.0776545 | 0.3472783 | 0.4429715 | 0.2045356 | 0.4942181 | 0.1661579 | -0.0520796 | 1.0000000 | 0.5022850 | 0.5206856 | 0.1789726 | 0.2818216 | 0.4038429 | 0.3913952 | 0.4459452 | -0.2293779 | 0.3244870 | -0.0896558 | -0.0758399 | 0.5388819 | 0.3928680 | 0.5244709 | 0.0436545 | 0.3016080 | 0.4885815 | 0.4698365 | 0.5385189 | 0.3117382 | 0.2482769 | 0.4417475 | -0.2520904 | 0.4397829 | 0.3413725 | -0.3279419 | 0.4854531 | 0.2312013 | 0.4841892 | 0.2979948 | 0.3670536 |
| ATT1_10_AttractPplAndEvents | 0.0760936 | 0.0814977 | 0.2674716 | 0.4876800 | 0.1821657 | 0.3714301 | 0.0937240 | -0.1485616 | 0.5022850 | 1.0000000 | 0.5235645 | 0.0993749 | 0.3326897 | 0.4626649 | 0.3811754 | 0.6130047 | -0.2588225 | 0.3476191 | -0.0997466 | -0.1291992 | 0.4452941 | 0.2820609 | 0.5811317 | -0.1367010 | 0.2825817 | 0.4091527 | 0.5430469 | 0.4736931 | 0.3240820 | 0.1639470 | 0.5365687 | -0.2417653 | 0.3960050 | 0.4959991 | -0.2776490 | 0.4367480 | 0.1414104 | 0.4262265 | 0.2030081 | 0.2852613 |
| ATT1_11_BodyRemembers | 0.1892129 | 0.0262516 | 0.3485551 | 0.5360377 | 0.0094967 | 0.5247270 | 0.2816853 | -0.1486377 | 0.5206856 | 0.5235645 | 1.0000000 | 0.1312519 | 0.4138740 | 0.4764432 | 0.4066875 | 0.5147970 | -0.2925920 | 0.3803597 | -0.1579940 | -0.1256117 | 0.4898779 | 0.4032909 | 0.5287270 | -0.0610542 | 0.3346039 | 0.4876131 | 0.6052014 | 0.5692964 | 0.3485249 | 0.3349171 | 0.6052088 | -0.1897516 | 0.5295881 | 0.4972222 | -0.3124592 | 0.5754526 | 0.2825870 | 0.5686156 | 0.3657404 | 0.3253450 |
| ATT1_12_WeakImmuneSystem | 0.1034782 | 0.1212355 | -0.0169306 | 0.1440485 | 0.1873449 | 0.2674479 | 0.0937958 | 0.0247272 | 0.1789726 | 0.0993749 | 0.1312519 | 1.0000000 | 0.2752603 | 0.0479077 | 0.0835712 | 0.0297011 | -0.0034640 | -0.0055184 | 0.2857657 | -0.0617796 | 0.3200732 | 0.1321390 | 0.0471601 | 0.3381754 | 0.1719405 | 0.1731542 | 0.0834863 | 0.2514190 | 0.2075617 | 0.0926864 | 0.1847677 | 0.1109876 | 0.2273381 | -0.0116188 | -0.0983390 | 0.1690157 | -0.0084918 | 0.2326579 | 0.0926467 | 0.0946424 |
| ATT1_13_ElectronicRadiation | 0.0197600 | 0.0694189 | 0.1413999 | 0.2358389 | -0.0446195 | 0.2621854 | 0.2443342 | -0.0167402 | 0.2818216 | 0.3326897 | 0.4138740 | 0.2752603 | 1.0000000 | 0.3555378 | 0.3075953 | 0.3902444 | -0.0504260 | 0.1899664 | -0.1472693 | 0.0383195 | 0.3629332 | 0.3639161 | 0.3729933 | 0.0443294 | 0.2510667 | 0.3453951 | 0.4484465 | 0.4734375 | 0.2937201 | 0.2040601 | 0.4658634 | -0.1298798 | 0.2325318 | 0.3497912 | -0.2163133 | 0.4491260 | 0.1815445 | 0.4567256 | 0.2382258 | 0.2388390 |
| ATT1_14_Reincarnation | 0.0730772 | -0.0522676 | 0.3188806 | 0.2801344 | -0.0713644 | 0.2540184 | 0.1965104 | -0.1849931 | 0.4038429 | 0.4626649 | 0.4764432 | 0.0479077 | 0.3555378 | 1.0000000 | 0.4727992 | 0.4949819 | -0.3822183 | 0.3720714 | -0.2446042 | -0.0097380 | 0.3700497 | 0.4332687 | 0.5763142 | -0.1813892 | 0.3351660 | 0.4559591 | 0.6405835 | 0.5220288 | 0.3426169 | 0.1475878 | 0.5489846 | -0.2995215 | 0.3574128 | 0.4116090 | -0.3735119 | 0.4033991 | 0.2505121 | 0.5153787 | 0.4316867 | 0.4462609 |
| ATT1_15_TrustAncientRemedies | 0.1222786 | -0.0062933 | 0.4925796 | 0.2823573 | -0.0171854 | 0.3298663 | 0.0586149 | -0.2613940 | 0.3913952 | 0.3811754 | 0.4066875 | 0.0835712 | 0.3075953 | 0.4727992 | 1.0000000 | 0.3855192 | -0.1294319 | 0.5828173 | 0.0266763 | -0.0932796 | 0.3212942 | 0.5331970 | 0.4771336 | -0.0234370 | 0.4961676 | 0.4796036 | 0.5500308 | 0.5508476 | 0.5334350 | 0.1872026 | 0.4559673 | -0.5413175 | 0.3699070 | 0.4266635 | -0.5217664 | 0.3437206 | 0.4094316 | 0.5057373 | 0.5679982 | 0.4669802 |
| ATT1_16_EverythingConnected | 0.1458379 | 0.0418795 | 0.2322353 | 0.4375893 | 0.0381642 | 0.4027674 | 0.0950937 | -0.1658542 | 0.4459452 | 0.6130047 | 0.5147970 | 0.0297011 | 0.3902444 | 0.4949819 | 0.3855192 | 1.0000000 | -0.2424026 | 0.3139141 | -0.2041912 | -0.1176678 | 0.4198273 | 0.3257879 | 0.6619870 | -0.1473315 | 0.2552401 | 0.3279818 | 0.5174101 | 0.4652473 | 0.2701384 | 0.2323531 | 0.5316003 | -0.1862762 | 0.4002202 | 0.4271042 | -0.2537242 | 0.4837864 | 0.1709845 | 0.4959438 | 0.2240387 | 0.2465442 |
| ATT1_17_SickByChance | 0.0062962 | 0.1082750 | -0.2312852 | -0.0647945 | 0.2457939 | -0.1979819 | -0.1742249 | 0.0969698 | -0.2293779 | -0.2588225 | -0.2925920 | -0.0034640 | -0.0504260 | -0.3822183 | -0.1294319 | -0.2424026 | 1.0000000 | -0.0547868 | 0.2497055 | 0.2709308 | -0.1708978 | -0.1182007 | -0.2521696 | 0.2942955 | -0.0583775 | -0.0383939 | -0.1873298 | -0.0814155 | -0.0474106 | -0.2829891 | -0.3211128 | 0.2435520 | -0.1002422 | -0.0726241 | 0.1893255 | -0.2876047 | -0.0235375 | -0.1934261 | -0.1167337 | -0.0729482 |
| ATT1_18_TreatsOnlySymptoms | 0.1090275 | -0.0678401 | 0.3851676 | 0.2574385 | -0.1112211 | 0.3487299 | 0.1239174 | -0.2789160 | 0.3244870 | 0.3476191 | 0.3803597 | -0.0055184 | 0.1899664 | 0.3720714 | 0.5828173 | 0.3139141 | -0.0547868 | 1.0000000 | -0.0509052 | -0.0661100 | 0.3849268 | 0.4861793 | 0.4526995 | -0.0914244 | 0.5365594 | 0.4514097 | 0.5846754 | 0.4430940 | 0.4434167 | 0.1410178 | 0.4160762 | -0.5366664 | 0.4022170 | 0.3760035 | -0.4209134 | 0.2675946 | 0.3751284 | 0.4160301 | 0.4353256 | 0.3681333 |
| ATT1_19_DoctorMustHealMe | 0.0362593 | 0.0841814 | 0.0061853 | -0.0264387 | 0.2337019 | -0.0609286 | -0.2131927 | 0.2018276 | -0.0896558 | -0.0997466 | -0.1579940 | 0.2857657 | -0.1472693 | -0.2446042 | 0.0266763 | -0.2041912 | 0.2497055 | -0.0509052 | 1.0000000 | 0.1102324 | -0.0046624 | -0.0665886 | -0.2321891 | 0.3033737 | 0.0750817 | 0.0334014 | -0.1645822 | -0.0908550 | 0.1426962 | -0.1049117 | -0.1679975 | 0.0919329 | -0.0536017 | -0.1017156 | 0.0349323 | -0.1275742 | 0.0517993 | -0.0990084 | 0.0563547 | -0.1921637 |
| ATT1_20_HealingIsLuck | -0.1254873 | -0.0273832 | -0.2851330 | -0.1218190 | 0.2034428 | -0.1203476 | -0.0270183 | 0.1247677 | -0.0758399 | -0.1291992 | -0.1256117 | -0.0617796 | 0.0383195 | -0.0097380 | -0.0932796 | -0.1176678 | 0.2709308 | -0.0661100 | 0.1102324 | 1.0000000 | -0.0613623 | -0.1051493 | 0.0239701 | 0.1910189 | -0.1271732 | 0.1051900 | 0.0429204 | -0.0055617 | -0.1255844 | -0.1137934 | -0.0714842 | 0.1369722 | 0.0012417 | -0.0746562 | 0.2071352 | -0.0280356 | 0.2436418 | 0.0034805 | -0.0795954 | -0.0577502 |
| ATT1_21_IllnessBecauseOfEmotions | 0.2249561 | -0.0240271 | 0.2227620 | 0.4357582 | 0.1415459 | 0.5529565 | 0.1236547 | -0.1018884 | 0.5388819 | 0.4452941 | 0.4898779 | 0.3200732 | 0.3629332 | 0.3700497 | 0.3212942 | 0.4198273 | -0.1708978 | 0.3849268 | -0.0046624 | -0.0613623 | 1.0000000 | 0.3456913 | 0.4929943 | 0.1545845 | 0.3394108 | 0.6272069 | 0.5051314 | 0.6357904 | 0.3311708 | 0.2190891 | 0.6680852 | -0.1926746 | 0.6436437 | 0.4242667 | -0.1779632 | 0.5839249 | 0.2156674 | 0.5067599 | 0.2591468 | 0.3053829 |
| ATT1_22_AvoidPharma | 0.1121921 | -0.0610453 | 0.3985563 | 0.2865663 | -0.1093726 | 0.3709777 | 0.2317797 | -0.2362467 | 0.3928680 | 0.2820609 | 0.4032909 | 0.1321390 | 0.3639161 | 0.4332687 | 0.5331970 | 0.3257879 | -0.1182007 | 0.4861793 | -0.0665886 | -0.1051493 | 0.3456913 | 1.0000000 | 0.4738300 | -0.0700838 | 0.4079969 | 0.4069011 | 0.4521505 | 0.4431287 | 0.4472165 | 0.2537590 | 0.4735388 | -0.4527800 | 0.3351502 | 0.2885399 | -0.5089255 | 0.4088550 | 0.2789144 | 0.4196286 | 0.5995711 | 0.4623255 |
| ATT1_23_NothingByChance | 0.1596211 | 0.0322213 | 0.3275579 | 0.4246552 | 0.0530034 | 0.4331098 | 0.1740472 | -0.2229017 | 0.5244709 | 0.5811317 | 0.5287270 | 0.0471601 | 0.3729933 | 0.5763142 | 0.4771336 | 0.6619870 | -0.2521696 | 0.4526995 | -0.2321891 | 0.0239701 | 0.4929943 | 0.4738300 | 1.0000000 | 0.0109790 | 0.3681791 | 0.5088340 | 0.5826668 | 0.5841888 | 0.4133183 | 0.1754654 | 0.6537926 | -0.2934296 | 0.4506522 | 0.3769215 | -0.3170201 | 0.4871373 | 0.2807297 | 0.6780911 | 0.3021821 | 0.4063435 |
| ATT1_24_IllnessBecauseOfGenes | -0.0164830 | 0.0786162 | -0.2124415 | -0.0219990 | 0.2104045 | 0.0769675 | -0.1791752 | 0.1715445 | 0.0436545 | -0.1367010 | -0.0610542 | 0.3381754 | 0.0443294 | -0.1813892 | -0.0234370 | -0.1473315 | 0.2942955 | -0.0914244 | 0.3033737 | 0.1910189 | 0.1545845 | -0.0700838 | 0.0109790 | 1.0000000 | -0.0270229 | 0.2135496 | -0.1242561 | 0.0472935 | -0.0074568 | 0.0309905 | -0.0371198 | 0.1354120 | 0.0457838 | -0.1547928 | 0.1830111 | 0.0267491 | 0.0755117 | -0.0103802 | -0.1452718 | -0.1160408 |
| ATT1_25_ChemotherapyHarmful | 0.1906475 | 0.1472411 | 0.3874647 | 0.2648194 | -0.0806387 | 0.3507904 | 0.1441873 | -0.2803159 | 0.3016080 | 0.2825817 | 0.3346039 | 0.1719405 | 0.2510667 | 0.3351660 | 0.4961676 | 0.2552401 | -0.0583775 | 0.5365594 | 0.0750817 | -0.1271732 | 0.3394108 | 0.4079969 | 0.3681791 | -0.0270229 | 1.0000000 | 0.4546396 | 0.4015689 | 0.4160576 | 0.8428863 | 0.1613083 | 0.3700511 | -0.3874451 | 0.3426574 | 0.1531717 | -0.3829592 | 0.3390217 | 0.2844477 | 0.3859409 | 0.4599611 | 0.3060069 |
| ATT1_26_HealingResultOfEmoDevelopment | 0.2045420 | 0.0347830 | 0.2926369 | 0.4122420 | 0.1341475 | 0.4152025 | 0.1831216 | -0.1360690 | 0.4885815 | 0.4091527 | 0.4876131 | 0.1731542 | 0.3453951 | 0.4559591 | 0.4796036 | 0.3279818 | -0.0383939 | 0.4514097 | 0.0334014 | 0.1051900 | 0.6272069 | 0.4069011 | 0.5088340 | 0.2135496 | 0.4546396 | 1.0000000 | 0.5238756 | 0.6860565 | 0.4238871 | 0.2454408 | 0.6083206 | -0.2645614 | 0.6146357 | 0.4278928 | -0.3004552 | 0.4424484 | 0.3652104 | 0.6161122 | 0.3447994 | 0.3893012 |
| ATT1_27_EnergeticSystemInBody | 0.1596584 | -0.0862025 | 0.3538216 | 0.3586105 | 0.0425695 | 0.4152410 | 0.2162358 | -0.2433245 | 0.4698365 | 0.5430469 | 0.6052014 | 0.0834863 | 0.4484465 | 0.6405835 | 0.5500308 | 0.5174101 | -0.1873298 | 0.5846754 | -0.1645822 | 0.0429204 | 0.5051314 | 0.4521505 | 0.5826668 | -0.1242561 | 0.4015689 | 0.5238756 | 1.0000000 | 0.7000795 | 0.3820224 | 0.2271138 | 0.6132902 | -0.3120822 | 0.5348839 | 0.6521425 | -0.4546381 | 0.5079048 | 0.4149599 | 0.6549123 | 0.4553830 | 0.4556764 |
| ATT1_28_ConfrontingEmotionalProb | 0.2316194 | -0.0507096 | 0.2801188 | 0.4398906 | 0.0881977 | 0.4767843 | 0.1749697 | -0.2243612 | 0.5385189 | 0.4736931 | 0.5692964 | 0.2514190 | 0.4734375 | 0.5220288 | 0.5508476 | 0.4652473 | -0.0814155 | 0.4430940 | -0.0908550 | -0.0055617 | 0.6357904 | 0.4431287 | 0.5841888 | 0.0472935 | 0.4160576 | 0.6860565 | 0.7000795 | 1.0000000 | 0.4046572 | 0.2143869 | 0.6510185 | -0.2109775 | 0.7099183 | 0.5365014 | -0.3740117 | 0.5366858 | 0.3231583 | 0.6910299 | 0.3852736 | 0.4165323 |
| ATT1_29_RadiationTherapyHarmful | 0.1872051 | 0.1495866 | 0.4184651 | 0.3409473 | 0.0095487 | 0.3305618 | 0.1290462 | -0.2923480 | 0.3117382 | 0.3240820 | 0.3485249 | 0.2075617 | 0.2937201 | 0.3426169 | 0.5334350 | 0.2701384 | -0.0474106 | 0.4434167 | 0.1426962 | -0.1255844 | 0.3311708 | 0.4472165 | 0.4133183 | -0.0074568 | 0.8428863 | 0.4238871 | 0.3820224 | 0.4046572 | 1.0000000 | 0.1547363 | 0.3815457 | -0.3602146 | 0.3113579 | 0.1294614 | -0.4278274 | 0.3487336 | 0.2931028 | 0.4152680 | 0.5058298 | 0.3417558 |
| ATT1_30_MandatoryVaccines | -0.0340306 | 0.0462063 | 0.2686508 | 0.1974204 | 0.1065393 | 0.2681004 | 0.0485263 | -0.1034996 | 0.2482769 | 0.1639470 | 0.3349171 | 0.0926864 | 0.2040601 | 0.1475878 | 0.1872026 | 0.2323531 | -0.2829891 | 0.1410178 | -0.1049117 | -0.1137934 | 0.2190891 | 0.2537590 | 0.1754654 | 0.0309905 | 0.1613083 | 0.2454408 | 0.2271138 | 0.2143869 | 0.1547363 | 1.0000000 | 0.1954700 | -0.3064897 | 0.1714389 | 0.0793773 | -0.2846922 | 0.2840609 | 0.3333933 | 0.2076523 | 0.2054123 | 0.1289035 |
| ATT1_31_IllnessSymbology | 0.1517998 | -0.0716466 | 0.3136477 | 0.3989796 | 0.0068710 | 0.5140983 | 0.2555365 | -0.2434594 | 0.4417475 | 0.5365687 | 0.6052088 | 0.1847677 | 0.4658634 | 0.5489846 | 0.4559673 | 0.5316003 | -0.3211128 | 0.4160762 | -0.1679975 | -0.0714842 | 0.6680852 | 0.4735388 | 0.6537926 | -0.0371198 | 0.3700511 | 0.6083206 | 0.6132902 | 0.6510185 | 0.3815457 | 0.1954700 | 1.0000000 | -0.2869571 | 0.5645111 | 0.4660545 | -0.3801909 | 0.5500127 | 0.1790779 | 0.6952910 | 0.4007775 | 0.4305977 |
| ATT1_32_TrustWesternDocs | -0.0290251 | -0.0212468 | -0.5087061 | -0.1081250 | 0.0294318 | -0.2432006 | -0.0503647 | 0.3172283 | -0.2520904 | -0.2417653 | -0.1897516 | 0.1109876 | -0.1298798 | -0.2995215 | -0.5413175 | -0.1862762 | 0.2435520 | -0.5366664 | 0.0919329 | 0.1369722 | -0.1926746 | -0.4527800 | -0.2934296 | 0.1354120 | -0.3874451 | -0.2645614 | -0.3120822 | -0.2109775 | -0.3602146 | -0.3064897 | -0.2869571 | 1.0000000 | -0.0889459 | -0.1661708 | 0.5801770 | -0.1927122 | -0.3233230 | -0.2108713 | -0.4836589 | -0.1966027 |
| ATT1_33_SymptomsWillDisappear | 0.1898578 | -0.0415685 | 0.1984842 | 0.4612814 | 0.1044473 | 0.4812476 | 0.1477357 | -0.1670566 | 0.4397829 | 0.3960050 | 0.5295881 | 0.2273381 | 0.2325318 | 0.3574128 | 0.3699070 | 0.4002202 | -0.1002422 | 0.4022170 | -0.0536017 | 0.0012417 | 0.6436437 | 0.3351502 | 0.4506522 | 0.0457838 | 0.3426574 | 0.6146357 | 0.5348839 | 0.7099183 | 0.3113579 | 0.1714389 | 0.5645111 | -0.0889459 | 1.0000000 | 0.4559997 | -0.2067542 | 0.5295790 | 0.2502046 | 0.6034346 | 0.3033756 | 0.3195752 |
| ATT1_34_EnergyInEastern | 0.0832831 | -0.0987391 | 0.2455830 | 0.3063318 | 0.0123156 | 0.3079574 | 0.0778997 | -0.1592532 | 0.3413725 | 0.4959991 | 0.4972222 | -0.0116188 | 0.3497912 | 0.4116090 | 0.4266635 | 0.4271042 | -0.0726241 | 0.3760035 | -0.1017156 | -0.0746562 | 0.4242667 | 0.2885399 | 0.3769215 | -0.1547928 | 0.1531717 | 0.4278928 | 0.6521425 | 0.5365014 | 0.1294614 | 0.0793773 | 0.4660545 | -0.1661708 | 0.4559997 | 1.0000000 | -0.2287806 | 0.3951118 | 0.1294561 | 0.4327702 | 0.2773837 | 0.2903717 |
| ATT1_35_SeriousSymptom | -0.1314154 | 0.0115117 | -0.5663668 | -0.2116695 | -0.0079130 | -0.2762678 | -0.1119189 | 0.4402867 | -0.3279419 | -0.2776490 | -0.3124592 | -0.0983390 | -0.2163133 | -0.3735119 | -0.5217664 | -0.2537242 | 0.1893255 | -0.4209134 | 0.0349323 | 0.2071352 | -0.1779632 | -0.5089255 | -0.3170201 | 0.1830111 | -0.3829592 | -0.3004552 | -0.4546381 | -0.3740117 | -0.4278274 | -0.2846922 | -0.3801909 | 0.5801770 | -0.2067542 | -0.2287806 | 1.0000000 | -0.1848200 | -0.2706797 | -0.3907500 | -0.6067400 | -0.4759387 |
| ATT1_36_UnprocessedTrauma | 0.0743992 | 0.0925523 | 0.2266169 | 0.4052624 | 0.0407223 | 0.5847060 | 0.2489982 | -0.0444246 | 0.4854531 | 0.4367480 | 0.5754526 | 0.1690157 | 0.4491260 | 0.4033991 | 0.3437206 | 0.4837864 | -0.2876047 | 0.2675946 | -0.1275742 | -0.0280356 | 0.5839249 | 0.4088550 | 0.4871373 | 0.0267491 | 0.3390217 | 0.4424484 | 0.5079048 | 0.5366858 | 0.3487336 | 0.2840609 | 0.5500127 | -0.1927122 | 0.5295790 | 0.3951118 | -0.1848200 | 1.0000000 | 0.1900231 | 0.5531866 | 0.3412182 | 0.3970854 |
| ATT1_37_NoBiopsy | 0.0377949 | -0.0252680 | 0.2334781 | 0.1882564 | 0.1606185 | 0.1759754 | 0.0698320 | -0.0619809 | 0.2312013 | 0.1414104 | 0.2825870 | -0.0084918 | 0.1815445 | 0.2505121 | 0.4094316 | 0.1709845 | -0.0235375 | 0.3751284 | 0.0517993 | 0.2436418 | 0.2156674 | 0.2789144 | 0.2807297 | 0.0755117 | 0.2844477 | 0.3652104 | 0.4149599 | 0.3231583 | 0.2931028 | 0.3333933 | 0.1790779 | -0.3233230 | 0.2502046 | 0.1294561 | -0.2706797 | 0.1900231 | 1.0000000 | 0.4094720 | 0.2964953 | 0.1801603 |
| ATT1_38_IllnessTeachesUs | 0.1966049 | -0.0220949 | 0.3287663 | 0.3545914 | 0.0722145 | 0.4818995 | 0.2527524 | -0.1714422 | 0.4841892 | 0.4262265 | 0.5686156 | 0.2326579 | 0.4567256 | 0.5153787 | 0.5057373 | 0.4959438 | -0.1934261 | 0.4160301 | -0.0990084 | 0.0034805 | 0.5067599 | 0.4196286 | 0.6780911 | -0.0103802 | 0.3859409 | 0.6161122 | 0.6549123 | 0.6910299 | 0.4152680 | 0.2076523 | 0.6952910 | -0.2108713 | 0.6034346 | 0.4327702 | -0.3907500 | 0.5531866 | 0.4094720 | 1.0000000 | 0.3786605 | 0.5594566 |
| ATT1_39_OnlyNatural | 0.1688695 | -0.0304308 | 0.4951061 | 0.2240950 | -0.0351267 | 0.2912395 | 0.1982211 | -0.2775466 | 0.2979948 | 0.2030081 | 0.3657404 | 0.0926467 | 0.2382258 | 0.4316867 | 0.5679982 | 0.2240387 | -0.1167337 | 0.4353256 | 0.0563547 | -0.0795954 | 0.2591468 | 0.5995711 | 0.3021821 | -0.1452718 | 0.4599611 | 0.3447994 | 0.4553830 | 0.3852736 | 0.5058298 | 0.2054123 | 0.4007775 | -0.4836589 | 0.3033756 | 0.2773837 | -0.6067400 | 0.3412182 | 0.2964953 | 0.3786605 | 1.0000000 | 0.5112160 |
| ATT1_40_StrongerComplaintsMeanHealing | 0.1461166 | -0.0737804 | 0.3783619 | 0.2303519 | -0.0293130 | 0.2816260 | 0.1957129 | -0.1582221 | 0.3670536 | 0.2852613 | 0.3253450 | 0.0946424 | 0.2388390 | 0.4462609 | 0.4669802 | 0.2465442 | -0.0729482 | 0.3681333 | -0.1921637 | -0.0577502 | 0.3053829 | 0.4623255 | 0.4063435 | -0.1160408 | 0.3060069 | 0.3893012 | 0.4556764 | 0.4165323 | 0.3417558 | 0.1289035 | 0.4305977 | -0.1966027 | 0.3195752 | 0.2903717 | -0.4759387 | 0.3970854 | 0.1801603 | 0.5594566 | 0.5112160 | 1.0000000 |
### Save to csv
write.csv(cors,
file=file.path(workingPath,
"correlations--bivariate--all-cases.csv"));
### http://www.sthda.com/english/wiki/ggcorrplot-visualization-of-a-correlation-matrix-using-ggplot2
ggcorrplot::ggcorrplot(cors);
ggcorrplot::ggcorrplot(cors,
method = "circle");
ggcorrplot(cors,
hc.order = TRUE,
outline.col = "white")
ggcorrplot::ggcorrplot(cors,
lab = TRUE);
for (xAxisVar in attitudeVars) {
ufs::cat0("\n\n#### ", xAxisVar,
" {.tabset .tabset-fade .tabset-pills}\n\n");
for (yAxisVar in tail(attitudeVars, -1)) {
### Only for 'half the matrix'
if (which(attitudeVars == yAxisVar) >
which(attitudeVars == xAxisVar)) {
ufs::cat0("\n\n##### ", yAxisVar,
"\n\n");
print(ggplot2::ggplot(data=dat,
mapping=ggplot2::aes_string(x=xAxisVar,
y=yAxisVar,
color='group_tri')) +
geom_jitter(size=3) +
theme_minimal());
}
}
}
For the network analysis section we will first estimate a full network where a choice of medical practice is regarded as a system component. This will allow us to explore how attitudes relate to the behavior of interest and the relative importance of each determinant. Afterwards, we will create sub samples based on a variable that represents groups of people that prefere one or other medical practice. This way we can investigate structural features of networks (topologies) that are peculiar to these groups.
# here I subset data that is going to be used in the network analysis with the behavior as a component.
subset <- dat[, c(attitudeVars,
"group_tri")];
# I eliminated other variables of interest (sex, age etc.) because the N in subgroups are very small and the number of "predictor" variables would exceed the number of datapoints.
### Here I create subsets based on the grouping variable.
for(i in levels(subset$group_tri)){
assign(paste("subset",
i,
sep = "_"),
subset(subset,
subset$group_tri == i))
}
subset$group_tri <-
as.numeric(subset$group_tri);
subset <-
subset %>% tidyr::drop_na();
network <-
estimateNetwork(subset,
default = "EBICglasso");
plot(network,
layout = 'spring',
labels = colnames(network),
title = c('Figure 1: A Network with the behavioral variable'));
### Also store to disk - Sam, you can copy this for any other plots of course
pdf(here::here('results-intermediate',
'network-with-grouping-variable.pdf'));
plot(network,
layout = 'spring',
labels = colnames(network),
title = c('Figure 1: A Network with the behavioral variable'));
dev.off();
# Calculating centrality measures.
pdf(here::here('results-intermediate',
'centrality_plot.pdf'));
centralityPlot(network,
include = "all");
dev.off();
# # Checking the stability of the centrality measures
# central_stability <-
# bootnet(network,
# nCores = 20,
# nBoots = 1000,
# type = 'case');
#
# pdf(here::here('results-intermediate',
# 'centrality_stability_plot.pdf'));
# plot(central_stability)
# dev.off();
#
# # Checking the stability/reliability of the edge weights
# edgewgt <-
# bootnet(network,
# nCores = 20,
# nBoots = 2500);
#
# plot(edgewgt,
# labels = FALSE,
# order = 'sample');
#
# pdf(here::here('results-intermediate',
# 'edge_weights.pdf'));
# plot(edgewgt,
# labels = FALSE,
# order = 'sample');
# dev.off();
Before applying Dijkstra’s algorithm we need to 1/the corelation matrix to invert it so the strongest connections will be represented with smaller numbers and the smallest correlations with larger.
### First we need to take the absoulte values of the adjacency matrix and devide 1 by the matrix. Then recreate a network object for further analysis.
absolute_adj <-
abs(network$graph);
for (i in which(absolute_adj > 0)) {
absolute_adj[i] = 1/absolute_adj[i]
}
graph_full <-
graph.adjacency(absolute_adj,
mode = 'undirected',
weighted = TRUE);
# Calculate shortest path to the outcome variable and then delete the last row of the dataframe that includes the outcome variable (shortest path to itself = 0)
dijkstra_fullnetwork <-
igraph::distances(graph_full,
v = V(graph_full),
to = 41,
algorithm = "dijkstra");
dijkstra_ful <-
subset(dijkstra_fullnetwork,
dijkstra_fullnetwork[,] == min(dijkstra_fullnetwork[-c(41),]));
Here we apply greedy hirarchical clustering algorithm to detect clusters in the data. Then we plot the results and the respective dendrogram.
fg <-
fastgreedy.community(graph_full, weights = E(graph_full)$weight)
fg$names <-
strtrim(fg$names, 7)
V(graph_full)$name <-
strtrim(fg$names, 7)
length(fg)
sizes(fg)
set.seed(100)
par(mfrow=c(1,2))
plot(fg, graph_full,
vertex.label.cex=c(0.5,0.5,0.5),
vertex.label.font=c(2))
dendPlot(fg, mode = 'phylo')
alternative <-
tidyr::drop_na(subset_Alternative[,-c(41)])
biomedical <-
tidyr::drop_na(subset_Biomed[,-c(41)])
network_fgl <-
EstimateGroupNetwork(list('Alternative' = alternative,
"Biomed" = biomedical)) # We get an empty network.
absolute_adj_hc <-
abs(network$graph);
graph_full_hc <-
graph.adjacency(absolute_adj[-c(41),-c(41)],
mode = 'undirected',
weighted = TRUE)
fg_item <-
fastgreedy.community(graph_full_hc,
weights = E(graph_full_hc)$weight,
cut_a)
fg_item <-
cut_at(fg_item,
no=10)
fg_item$names <-
strtrim(fg_item$names, 7)
V(graph_full_hc)$name <-
strtrim(fg_item$names, 7)
length(fg_item)
sizes(fg_item)
set.seed(101)
par(mfrow=c(1,2))
plot(fg_item, graph_full_hc,
vertex.label.cex=c(0.5,0.5,0.5),
vertex.label.font=c(2))
dendPlot(fg_item, mode = 'phylo')
###
### attitudeVars
###
lapply(1:20,
function(x)
return(attitudeVars[which(cut_at(fg_item,
no=20)==x)]));
### Trying to cut the inductive dendrogram
walk <- g %>%
cluster_walktrap() %>%
cut_at(no = 10)
eb <- g %>%
cluster_edge_betweenness() %>%
cut_at(no = 10)